Open Circuit Fault Diagnosis in Induction Motor Driver Inverter

Abstract

The induction machines are the power horses in the industry due to the practically null maintenance, this kind of machines are use in a widely group of industrial applications, and with the advance of power electronics these machines replace another kind, like direct current (dc) motors attributable to the evolution of control algorithms and the digital platforms. In this context, a methodology is proposed to detect and isolate faults, focusing on the inverter stage of Induction Machine motor drives, with a specific emphasis on Insulated Gate Bipolar Transistor (IGBT) faults, using phasor analysis and fuzzy logic. This methodology has demonstrated effective performance in detecting and isolating different types of electrical faults, such as stator inter-turn short-circuit. In this case, damaged switching IGBTs were identified using low computational resources. This research was motivated because some complex techniques like music (multiple signal classifier), dynamic observers, techniques based on mathematical models, statistics techniques, optimization techniques, AI techniques like deep learning, vector support machines, genetic algorithms, and so on, require a great quantity of data and or computer processing. Thanks to this scheme, it is possible to implement a low cost computational platform based on a TI DSP TMS320F28335 processor for a real-time fault diagnosis in Induction Machine inverter.